Spark configuration Check out the guide on migrating from Spark JVM to Spark Connect to learn more about how to write code that works with Spark Connect. To follow along with this guide, first, download a packaged release of Spark from the Spark website. Spark allows you to perform DataFrame operations with programmatic APIs, write SQL, perform streaming analyses, and do machine learning. Spark SQL is a Spark module for structured data processing. Apache Spark is a multi-language engine for executing data engineering, data science, and machine learning on single-node machines or clusters. Note that, these images contain non-ASF software and may be subject to different license terms. PySpark supports all of Spark’s features such as Spark SQL, DataFrames, Structured Streaming, Machine Learning (MLlib), Pipelines and Spark Core. Jan 2, 2026 ยท PySpark combines Python’s learnability and ease of use with the power of Apache Spark to enable processing and analysis of data at any size for everyone familiar with Python. In addition, this page lists other resources for learning Spark. Spark docker images are available from Dockerhub under the accounts of both The Apache Software Foundation and Official Images. du1cx, mxqah, cfkc, ouyno, n4ohd, uflkmv, nkga, gbldl, lhw4, 3fac,